Results 1 to 10 of about 683,774 (325)
Dependence-Robust Confidence Intervals for Capture-Recapture Surveys. [PDF]
J Surv Stat Methodol, 2023 Abstract Capture–recapture (CRC) surveys are used to estimate the size of a population whose members cannot be enumerated directly. CRC surveys have been used to estimate the number of Coronavirus Disease 2019 (COVID-19) infections, people who use drugs, sex workers, conflict casualties, and trafficking victims.
Sun J +3 more
europepmc +6 more sources
Robust Confidence Intervals for PM2.5 Concentration Measurements in the Ecuadorian Park La Carolina. [PDF]
Sensors (Basel), 2020 In this article, robust confidence intervals for PM2.5 (particles with size less than or equal to 2.5 μ m ) concentration measurements performed in La Carolina Park, Quito, Ecuador, have been built.
Hernandez W +3 more
europepmc +4 more sources
Bootstrapping Confidence Intervals For Robust Measures Of Association [PDF]
Journal of Modern Applied Statistical Methods, 2003 A Monte Carlo simulation study compared four bootstrapping procedures in generating confidence intervals for the robust Winsorized and percentage bend correlations.
King, Jason E.
core +5 more sources
Robust Empirical Bayes Confidence Intervals [PDF]
Econometrica, 2022 We construct robust empirical Bayes confidence intervals (EBCIs) in a normal means problem. The intervals are centered at the usual linear empirical Bayes estimator, but use a critical value accounting for shrinkage. Parametric EBCIs that assume a normal distribution for the means (Morris (1983b)) may substantially undercover when this assumption is ...
Timothy B. Armstrong +2 more
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Robust Method for Confidence Interval Estimation in Outlier-Prone Datasets: Application to Molecular and Biophysical Data [PDF]
BiomoleculesEstimating confidence intervals in small or noisy datasets is a recurring challenge in biomolecular research, particularly when data contain outliers or exhibit high variability.
Victor V. Golovko
doaj +2 more sources
Robust misinterpretation of confidence intervals
Psychonomic Bulletin & Review, 2014 Null hypothesis significance testing (NHST) is undoubtedly the most common inferential technique used to justify claims in the social sciences. However, even staunch defenders of NHST agree that its outcomes are often misinterpreted. Confidence intervals (CIs) have frequently been proposed as a more useful alternative to NHST, and their use is strongly
Rink Hoekstra +3 more
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ROCKET: Robust Confidence Intervals via Kendall's Tau for\n Transelliptical Graphical Models [PDF]
The Annals of Statistics, 2015 Undirected graphical models are used extensively in the biological and social sciences to encode a pattern of conditional independences between variables, where the absence of an edge between two nodes $a$ and $b$ indicates that the corresponding two variables $X_a$ and $X_b$ are believed to be conditionally independent, after controlling for all other
Rina Foygel Barber, Mladen Kolar
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On the Binomial Confidence Interval and Probabilistic Robust Control [PDF]
Automatica, 2008 6 pages, 1 ...
Xinjia Chen, Kemin Zhou, J.L. Aravena
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Clinical Chemistry Reference Intervals for Health Assessment in Wild Adult Harbour Seals. [PDF]
Animals (Basel)Reference intervals for clinical chemistry blood parameters are valuable for both individual diagnostics for animals in managed or veterinary care, and for evaluating wild population health.
Hall AJ +6 more
europepmc +2 more sources
Journal of Modern Applied Statistical Methods, 2020 In this paper, three robust confidence intervals are proposed as alternatives to the Student t confidence interval. The performance of these intervals was compared through a simulation study shows that Qn-t confidence interval performs the best and it is as good as Student’s t confidence interval. Real-life data was used for illustration and performing
Jennifer E. V. Lloyd +8 more
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